The demand for robust biometrics is high in today's security-conscious society. Known solutions include fingerprint identification, iris scanning, facial recognition, etc. However, drawbacks of known solutions include the fact that anatomies utilized in such approaches are external to the body and subject to corruption via intentional injury. For example, there have been instances, where artificial fingerprints have been used to circumvent biometric security systems. In other biometrics modalities, similar attacks are possible, such as face masks to hide identity, and designer iris lenses to fool iris recognition systems.
Other approaches suggest that electrocardiography (ECG or EKG) signals or acoustic heartbeats offer uniqueness, but theses items have less information content than images, such as short-axis cardiac magnetic resonance imaging (MRI) images, which directly sense the anatomical geometry. Also, cardiac EKG may have fewer unique identifying characteristics to quantify because it assesses electrical activity of the heart, which is one-dimensional (1D) in nature.
Accordingly, more secure biometrics are needed.